DST can be used with any one-shot, optimization-based style transfer method with a content loss and a style loss. We evaluate its effects when combined with the original neural style transfer algorithm of Gatys [1]} and STROTSS. Each method defines a content loss \(L_{\text{content}}(C,O)\)  and a style loss \(L_{\text{style}}(S,O)\) . When using DST with a base style transfer method, we do not change anything about \(L_{\text{content}}\) . The style loss of DST is composed of two terms
\(L_{\text{style}}(S, O) + L_{\text{style}}(S, W(O, \theta )).\) 
